941
Views
5
CrossRef citations to date
0
Altmetric
Original Articles

Is there a relationship between hematological parameters and duration of respiratory events in severe OSA

ORCID Icon & ORCID Icon
Pages 125-131 | Received 10 Jul 2019, Accepted 03 Aug 2019, Published online: 14 Aug 2019

Abstract

Aim: The aim of this study was to compare hematological parameters with the mean obstructive apnea duration (MOAD), mean mixed apnea duration (MMAD), mean central apnea duration (MCAD), mean total apnea duration (MTAD) and mean hypopnea duration (MHD), and blood oxygenation, other polysomnographic sleep parameters in patients with severe OSA.

Material and methods: A retrospective study included 120 patients with severe OSA. The correlations between the hematological parameters with MOAD, MMAD, MCAD, MTAD, MHD, and blood oxygenation, other polysomnographic sleep parameters were analyzed.

Results: There was a positive correlation between hgb with MOAD, MMAD, MTAD MCAD, MHD; mean oxygen desaturation, and the number of desaturation (≥5%). Also, hgb associated negatively with N1 sleep, WASO (wake time after sleep onset) and positively with REM, N2 sleep, total sleep time, and sleep efficiency. RDW and MOAD, MTAD, MHD were negatively related. Also, RDW related positively with sleep latency, WASO, and N1 sleep; negatively with sleep efficiency and REM sleep. There was no relationship between duration of respiratory events with NLR, PRL, and MPV.

Conclusions: Hematological parameters, especially hgb and RDW, can be used to assess the severity of the disease in severe OSA patients in addition to AHI.

Introduction

Obstructive sleep apnea (OSA) is characterized by recurrent partial or total obstruction of the upper airway which leads to subsequent paroxysmal nocturnal hypoxia, intermittent arousals, and excessive daytime sleepiness. The apnea-hypopnea index (AHI) is the number of apneas and hypopneas recorded during the polysomnography (PSG) per hour of sleep. AHI has been used as the main parameter to diagnose and classify the severity of the disease. Based on the AHI, the severity of OSA is classified as: normal, AHI <5; mild, 5 ≤ AHI < 15; moderate, 15 ≤ AHI < 30; and severe, AHI ≥ 30 events per hour. Because AHI is a quantitative parameter and does not contain information about the morphology and duration of the respiratory events and related oxygen desaturations, different parameters determining the severity of OSAS, in addition to AHI, have been studied [Citation1–3]. The mean apnea-hypopnea duration (MAD) is one of the indicators of the severity of respiratory events during sleep. Zhan et al. [Citation2] showed that for patients with severe OSA, the MAD was an indicator of levels of blood oxygenation and sleep parameters. Also, MAD had been studied separately as the mean obstructive apnea duration (MOAD), mean mixed apnea duration (MMAD), mean central apnea duration (MCAD), mean total apnea duration (MTAD) and mean hypopnea duration (MHD) to determine the severity of the disease in more detail [Citation3].

OSA has been shown to increase the risk for systemic hypertension, pulmonary vascular disease, ischemic heart disease, cerebral vascular disease, congestive heart failure, and arrhythmias. Additionally, it was reported that sexual problems are common among men with OSA and sleep disturbance is one of the clinical signs for severe hypogonadism [Citation4–6]. OSA is associated with systemic inflammation and oxidative stress [Citation7]. Thiol/disulfide homeostasis, an indicator of oxidative stress, has also been shown to be impaired [Citation8]. Inflammatory markers are useful to assess the severity of disease and predict the presence of complications in OSA patients [Citation9]. Red blood cell distribution width (RDW) is a numerical measure of the size variability of circulating erythrocytes. RDW has been reported as a strong independent predictor of adverse outcomes in the general population and also high RDW associated with cardiovascular disease (CVD), acute coronary syndrome, heart failure, prehypertension and hypertension, OSA, metabolic syndrome, and microvascular and macrovascular complications of diabetes [Citation10–17]. RDW is also reported to be increased with inflammation in OSA [Citation18–22]. Recent studies suggest that NLR is a good indicator of inflammation. OSA is associated with a high level of NLR [Citation19–21,Citation23,Citation24]. PLR is an inflammatory marker to predict the adverse outcomes of CVD. OSA was associated with a higher level of PLR and hematocrit (htc) [Citation19,Citation20,Citation25]. Higher htc levels may be due to secondary erythropoiesis. Platelet is activated and aggregated in patients with OSA, which is also related to systemic inflammation [Citation26,Citation27]. MPV and PDW are both useful markers of platelet activity.

Although there are many studies about the relationship between hematological parameters and OSA, the relationship between the duration of respiratory events and hematological parameters has not been studied before. Therefore, this study aimed to compare the MOAD, MMAD, MCAD, MTAD, and MHD with the hematological parameters in patients diagnosed with severe OSA.

Material and methods

Patients and study design

A retrospective clinical study included 120 severe OSA patients who were >18 years of age. The diagnosis of OSA by PSG was supported with the use of the AHI of >5 events per hour, as recommended by the diagnostic criteria of the American Academy of Sleep Medicine (AASM). Demographic parameters were extracted from the patient medical records. The study protocol was approved by the ethics committee, and informed consent was obtained from all subjects who participated in the study.

Polysomnography

PSG in the sleep laboratory included continuous electroencephalographic (EEG) polygraphic recording using EEG leads, the use of right and left electro-oculographic leads, and chin electromyography for sleep staging. Electrocardiography (ECG) monitoring during sleep, airflow measurement at the nose and mouth, and chest and abdominal respiratory movements were measured during sleep. Arterial oxygen saturation was measured with pulse oximetry. All sleep studies were interpreted according to the manual of the AASM for the Scoring of Sleep, by certified sleep physicians. Apnea was identified when the airflow amplitude in the nasal cannula was <10% of baseline and when no flow occurred on the oral airflow sensor (thermistor). Hypopneas were identified when the amplitude of the airflow was reduced by 30%, the event was followed by a 4% desaturation. The AHI was defined as the total number of apnea and hypopnea events per hour of sleep.

Biochemical measurements

Blood samples were obtained from venous blood samples drawn after a 12 h fasting period. The hematological parameters (complete blood count) were measured in a blood sample collected in dipotassium ethylenediaminetetraacetic acid (EDTA) tubes within 30 min. NLR was calculated by dividing neutrophil count by lymphocyte count. PLR was calculated by dividing platelet count by lymphocyte count.

Statistical analysis

Data were expressed as the mean ± standard deviation (SD) or the median (interquartile range). The correlations between the hematological parameters and MOAD, MMAD, MCAD, MTAD, MHD, patient demographic parameters, blood oxygenation, other polysomnographic sleep parameters were analyzed in patients with severe OSA. Correlations were tested using Pearson's correlation (normal distribution) and Spearman correlation (non-normal distribution). Data were analyzed using IBM SPSS statistics 22.0 (SPSS Inc., Chicago, IL, USA). The value of p < 0.05 was considered as statistically significant.

Results

Baseline demographics

Our retrospective study included 120 patients with severe OSA. The mean age of the patients was 51.01 ± 11.45. The demographic characteristics of the study population are summarized ().

Table 1. The demographic characteristics of the study population.

Characteristics of the hematological parameters

While hgb, RDW, PDW, NLR, and PLR showed non-normal distribution, MPV showed normal distribution. The median hgb was 14.3 (min–max: 8.5–17.1), median RDW was 13.6 (min–max: 9.7–28.2), median PDW was 16.5 (min–max: 15.3–19.4), median NLR was 1.81 (0.34–13.5), median PLR was 104.5 (min–max: 44.3–536.7) for all patients in the study. Mean MPV was 8.7 ± 1.2. There was no relationship between hgb, RDW, PDW, NLR, PLR, MPV and AHI, REM-AHI/NREM-AHI.

Relationship of hematological parameters and MOAD, MMAD, MSAD, MTAD, MHD

The relationship of hematological parameters and MOAD, MMAD, MSAD, MTAD, MHD is summarized ().

Table 2. The relationship of hematological parameters and MOAD, MMAD, MSAD, MTAD, MHD.

Relationship of hematological parameters and polysomnographic sleep parameters

The relationship of hematological parameters and polysomnographic sleep parameters is summarized ().

Table 3. The relationship of hematological parameters and polysomnographic sleep parameters.

Relationship of hematological parameters and blood oxygen parameters

The relationship of hematological parameters and blood oxygen parameters during PSG is summarized ().

Table 4. The relationship of hematological parameters and blood oxygen parameters.

Relationship of hematological parameters with blood oxygen parameters and polysomnographic sleep parameters in the patients ≤50 years old

The relationship of hematological parameters with blood oxygen parameters and polysomnographic sleep parameters in the patients ≤50 years old during PSG is summarized ().

Table 5. The relationship of hematological parameters with blood oxygen parameters and polysomnographic sleep parameters in the patients ≤50 years old.

Discussion

Inflammatory markers are useful to assess the degree of inflammation and predict the presence of complications in OSA patients. It is possible to use a wide range of markers to demonstrate systemic inflammation. Due to being cost-effective and easily accessible, hematological parameters used as a marker as an indicator of the prognosis and systemic inflammation. RDW, PDW, NLR, PLR, and MPV are hematological parameters that have been studied in OSA as inflammatory markers. This is the first study that has investigated the relationship between hematological parameters with MAD separately as MOAD, MMAD, MCAD, MTAD, MHD and blood oxygenation, polysomnographic sleep parameters in severe OSA patients.

There was a positive moderate correlation between MOAD, MMAD, MTAD, and hgb; a positive weak correlation between MCAD, MHD, and hgb. Also, there was a positive moderate correlation between hgb with mean oxygen desaturation and the number of desaturation (≥5%). Prolonged respiratory events especially obstructive ones, lead to deeper oxygen saturation which may lead to increased hgb levels. However, hgb levels were still within the normal range. According to the current OSAS classification, although there was no relationship between hgb level and OSAS severity; duration of respiratory events and hgb level was related. Several mechanisms could explain the increment of hgb in patients with severe OSA. Two possible mechanisms are erythropoiesis driven by oxygen desaturation and hemoconcentration by plasma volume change. Erythropoietin (EPO), a key mediator of erythropoiesis, regulates the red blood cell mass. However, it remains unclear whether OSA is associated with elevated EPO. Winnicki et al. [Citation28] recently reported that EPO was increased only in patients with severe OSA, and high levels of EPO return to baseline after effective treatment with CPAP. The inclusion of patients with mild to moderate OSA may blur the increase in EPO evident in patients with severe OSA. Ciftci TU et al. [Citation29] did not find a significant increase in EPO levels in their study which include 69 moderate and severe OSAS patients. A possible explanation of increased EPO in severe OSAS but not in moderate and mild OSAS could be that the patients with severe OSA may be exposed to a sufficient cumulative period of sustained hypoxia during sleep. Thus, EPO could be playing a role in the higher htc seen in severe OSA. This finding was consistent with our study. One of the possible mechanisms is hemoconcentration by plasma volume change. Krieger et al. [Citation30] suggest that the increase in htc level in OSA is related to hemoconcentration resulting from fluid shifts from the intravascular to the extravascular bed. These fluid shifts may be caused by atrial natriuretic peptide, which correlates with the severity of sleep apnea and hypoxemia and is reduced after treatment with CPAP. On the other hand, according to our study, high levels of hgb associated with lower N1 sleep, WASO (wake time after sleep onset); higher REM and N2 sleep, higher total sleep time and sleep efficiency. When the depth and duration of the apnea attacks increase, AHI may paradoxically fall [Citation1]. Patients with longer apnea had less number of awakenings during all sleep. Time spent more during apnea/hypopnea with the same total sleep time, could lead to fewer awakenings paradoxically. As a result higher MOAD and MTAD lead to lower N1 sleep and WASO; higher REM and N2 sleep, higher total sleep time and sleep efficiency. The effect of hgb on sleep configuration could be explained by its relationship with the duration of obstructive respiratory events.

Oxidative stress and inflammation were shown to be related to RDW. RDW has been a strong predictor of all-cause mortality in population cohorts [Citation10]. Increased RDW may affect the outcomes in chronically ill patients, regardless of anemia status [Citation11–17]. The relationship between RDW and cardiovascular and pulmonary diseases may be due to inflammation. Both inflammation and oxidative stress have been known to play major roles in the pathogenesis of OSAS. While some studies have reported a positive relationship between RDW and AHI, others did not find any relationship. We showed a negative relationship between RDW and MOAD, MTAD and MHD. The explanation of this relationship could be that longer apnea leads to paradoxically fall in AHI [Citation1]. After correction for anemia, RDW was still negatively correlated with MOAD, MTAD, and MHD. Also, RDW related positively with sleep latency, WASO, and N1 sleep; negatively with sleep efficiency and REM sleep. The effect of RDW on sleep configuration may be due to its relation with apnea duration. It was reported that higher apnea duration is associated with higher N1 sleep and WASO; lower REM and N2 sleep.

According to our study, RDW and PDW significantly increased with the severity of OSA in the patients ≤ 50 years old, the relationship between the severity of OSA and PDW was stronger. Additionally higher RDW and PDW were associated with deeper desaturations in the patients ≤ 50years old. Similarly, Saygın et al. [Citation26] reported that PDW values correlate with AHI in the patients <40 years old with CVD. There was no cardiovascular risk assessment in the protocol of our study. Further studies are needed to investigate the possibility that RDW and PDW values are related to the severity of OSAS in these patients due to cardiovascular risk.

Although there are studies reported that OSAS is associated with a higher level of PLR, NLR, and MPV we did not found any relationship between PLR, NLR, and MPV with OSA severity and also the duration of respiratory events [Citation25,Citation31]. Only higher NLR was associated with longer total apnea duration in the patients ≤ 50 years old.

The present study has some limitations. It was retrospective, performed in a single-center, and included a relatively small study population. Evaluation of the hematological parameters as inflammatory markers to assess the severity of OSA is still a need for further prospective, large scale, controlled studies.

The findings of this study showed that hematological parameters can be used to assess the severity of the disease in severe OSAS patients in addition to AHI. In severe OSAS patients with longer respiratory events (especially obstructive ones) and deeper desaturations, hgb values are higher, independent of AHI. Hgb and RDW may influence the duration of respiratory events and as a result, change sleep configuration. RDW and PDW are also associated with disease severity in severe OSA patients under 50 years of age.

Disclosure statement

Views expressed in the submitted article are our own and not an official position of the institution or funder.

The authors have no conflict of interest to declare.

References

  • Kulkas A, Tiihonen P, Julkunen P, et al. Novel parameters indicate significant differences in severity of obstructive sleep apnea with patients having similar apnea-hypopnea index. Med Biol Eng Comput. 2013;51:697–708.
  • Zhan X, Fang F, Wu C, et al. Retrospective study to compare the use of the mean apnea-hypopnea duration and the apnea-hypopnea index with blood oxygenation and sleep patterns in patients with obstructive sleep apnea diagnosed by polysomnography. Med Sci Monit. 2018;24:1887–1893.
  • Yılmaz Durmaz D, Güneş A. Which is more important: the number or duration of respiratory events to determine the severity of obstructive sleep apnea? Aging Male. 2019;1–6.
  • Taken K, Ekin S, Arısoy A, et al. Erectile dysfunction is a marker for obstructive sleep apnea. Aging Male. 2016;19:102–105.
  • Li X, Dong Z, Wan Y, et al. Sildenafil versus continuous positive airway pressure for erectile dysfunction in men with obstructive sleep apnea: a meta-analysis. Aging Male. 2010;13:82–86.
  • Shigehara K, Konaka H, Sugimoto K, et al. Sleep disturbance as a clinical sign for severe hypogonadism: efficacy of testosterone replacement therapy on sleep disturbance among hypogonadal men without obstructive sleep apnea. Aging Male. 2018;21:99–105.
  • Hopps E, Caimi G. Obstructive sleep apnea syndrome: links betwen pathophysiology and cardiovascular complications. CIM. 2015;38:362–370.
  • Sengoren Dikis O, Acat M, Casim H, et al. The relationship of thiol/disulfide homeostasis in the etiology of patients with obstructive sleep apnea: a case-control study. Aging Male. 2019;1–8.
  • Nadeem R, Molnar J, Madbouly EM, et al. Serum inflammatory markers in obstructive sleep apnea: a metaanalysis. J Clin Sleep Med. 2013;9:1003–1012.
  • Cavusoglu E, Chopra V, Gupta A, et al. Relation between red blood cell distribution width (RDW) and all-cause mortality at two years in an unselected population referred for coronary angiography. Int J Cardiol. 2010;141:141–146.
  • Dabbah S, Hammerman H, Markiewicz W, et al. Relation between red cell distribution width and clinical outcomes after acute myocardial infarction. Am J Cardiol. 2010;105:312–317.
  • Felker GM, Allen LA, Pocock SJ, CHARM Investigators, et al. Red cell distribution width as a novel prognostic marker in heart failure: data from the CHARM Program and the Duke Databank. J Am Coll Cardiol. 2007;50:40–47.
  • Al-Najjar Y, Goode KM, Zhang J, et al. Red cell distribution width: an inexpensive and powerful prognostic marker in heart failure. Eur J Heart Fail. 2009;11:1155–1162.
  • Tanindi A, Topal FE, Topal F, et al. Red cell distribution width in patients with prehypertension and hypertension. Blood Press. 2012;21:177–181.
  • Ozsu S, Abul Y, Gulsoy A, et al. Red cell distribution width in patients with obstructive sleep apnea syndrome. Lung. 2012;190:319–326.
  • SáNchez-Chaparro MA, Calvo-Bonacho E, GonzáLez-Quintela A, et al. Higher red blood cell distribution width is associated with the metabolic syndrome: results of the Ibermutuamur Cardiovascular Risk assessment study. Diabetes Care. 2010;33:e40.
  • Malandrino N, Wu WC, Taveira TH, et al. Association between red blood cell distribution width and macrovascular and microvascular complications in diabetes. Diabetologia. 2012;55:226–235.
  • Sunnetcioglu A, Gunbatar H, Yildiz H. Red cell distribution width and uric acid in patients with obstructive sleep apnea. Clin Respir J. 2018;12:1046–1052.
  • Song YJ, Kwon JH, Kim JY, et al. The platelet-to-lymphocyte ratio reflects the severity of obstructive sleep apnea syndrome and concurrent hypertension. Clin Hypertens. 2015;22:1.
  • Koseoglu HI, Altunkas F, Kanbay A, et al. Platelet-lymphocyte ratio is an independent predictor for cardiovascular disease in obstructive sleep apnea syndrome. J Thromb Thrombolysis. 2015;39:179–185.
  • Uygur F, Tanriverdi H, Aktop Z, et al. The neutrophil-tolymphocyte ratio in patients with obstructive sleep apnoea syndrome and its relationship with cardiovascular disease. Heart Lung. 2016;45:121–125.
  • Kurt OK, Yildiz N. The importance of laboratory parameters in patients with obstructive sleep apnea syndrome. Blood Coagul Fibrinolysis. 2013;24:371–374.
  • Yenigun A, Karamanli H. Investigation of the relationship between neutrophil-to-lymphocyte ratio and obstructive sleep apnoea syndrome. J Laryngol Otol. 2015;129:887–892.
  • Korkmaz M, Korkmaz H, Kucuker F, et al. Evaluation of the association of sleep apnea-related systemic inflammation with CRP, ESR, and neutrophil-tolymphocyte ratio. Med Sci Monit. 2015;21:477–481.
  • Koseoglu S, Ozcan KM, Ikinciogullari A, et al. Relationship between neutrophil to lymphocyte ratio, platelet to lymphocyte ratio and obstructive sleep apnea syndrome. Adv Clin Exp Med. 2015;24:623–627.
  • Saygin M, Ozturk O, Ozguner MF, et al. Hematological parameters as predictors of cardiovascular disease in obstructive sleep apnea syndrome patients. Angiology. 2016;67:461–470.
  • Kondo Y, Kuwahira I, Shimizu M, et al. Significant relationship between platelet activation and apnea-hypopnea index in patients with obstructive sleep apnea syndrome. Tokai J Exp Clin Med. 2011;36:79–83.
  • Winnicki M, Shamsuzzaman A, Lanfranchi P, et al. Erythropoietin and obstructive sleep apnea. Am J Hypertens. 2004;17:783–786.
  • Ciftci TU, Kokturk O, Demirtas S, et al. Consequences of hypoxia-reoxygenation phenomena in patients with obstructive sleep apnea syndrome. Ann Saudi Med. 2011;31:14–18.
  • Krieger J, Sforza E, Barthelmebs M, et al. Overnight decrease in hematocrit after nasal CPAP treatment in patients with OSA. Chest. 1990;97:729–730.
  • Sökücü SN, Ozdemir C, Dalar L, et al. Is mean platelet volume really a severity marker for obstructive sleep apnea syndrome without comorbidities? Pulm Med. 2014;2014:1.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.